Creating a text classifier to detect radiology reports describing mediastinal findings associated with inhalational anthrax and other disorders
Creating a text classifier to detect radiology reports describing mediastinal findings associated with inhalational anthrax and other disorders
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DOI：
10.1197/jamia.m1330
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发表时间：
2003-09-01
影响因子：
6.4
通讯作者：
Wagner, MM
中科院分区：
文献类型：
--
作者：
Chapman, WW;Cooper, GF;Wagner, MM
目的：本研究的目的是创建一个用于自动检测与吸入性炭疽纵隔发现一致的胸片报告的分类器。设计：作者使用识别患者集（IPS）系统创建一个用于检测描述与炭疽一致的纵隔发现的报告的关键词分类器，并在79，032份胸片报告的测试集上比较其性能。ROC曲线下面积是IPS分类器的主要结果测量。初始IPS模型的敏感性和特异性进行了计算，根据现有的关键字搜索，并对布尔版本的IPS classific.Results：IPS分类器收到的ROC曲线下面积为0.677（90%CI = 0.628至0.772），特异性为0.99，最大灵敏度为0.35。初始IPS模型的特异性为1.0，敏感性为0.04。结论：IPS系统是一个有用的工具，可以帮助领域专家创建文本报告的统计关键词分类器，这是一个潜在的有用组件，用于监测X线检查结果可疑炭疽。
Objective: The aim of this study was to create a classifier for automatic detection of chest radiograph reports consistent with the mediastinal findings of inhalational anthrax.Design: The authors used the Identify Patient Sets (IPS) system to create a key word classifier for detecting reports describing mediastinal findings consistent with anthrax and compared their performances on a test set of 79,032 chest radiograph reports.Measurements: Area under the ROC curve was the main outcome measure of the IPS classifier. Sensitivity and specificity of an initial IPS model were calculated based on an existing key word search and were compared against a Boolean version of the IPS classifier.Results: The IPS classifier received an area under the ROC curve of 0.677 (90% Cl = 0.628 to 0.772) with a specificity of 0.99 and maximum sensitivity of 0.35. The initial IPS model attained a specificity of 1.0 and a sensitivity of 0.04.Conclusion: The IPS system is a useful tool for helping domain experts create a statistical key word classifier for textual reports that is a potentially useful component in surveillance of radiographic findings suspicious for anthrax.